Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
The existing landslide monitoring methods are unable to accurately reflect the true deformation of the landslide body, and the use of a single SAR satellite, affected by its revisit cycle, still suffers from the limitation of insufficient temporal resolution for landslide monitoring. Therefore, this paper proposes a method for the dynamic reconstruction and evolutionary characteristic analysis of the Gaojiawan landslide's along-slope deformation based on ascending and descending orbit time-series InSAR observations using Kalman filtering. Initially, the method employs a gridded selection approach during the InSAR time-series processing, filtering coherent points based on the standard deviation of residual phases, thereby ensuring the density and quality of the extracted coherent points. Subsequently, the combination of ascending and descending orbit data converts the landslide's line of sight (LOS) deformation into along-slope deformation. Finally, the Kalman filtering method is utilized for dynamic reconstruction of the landslide deformation, and an analysis of the evolutionary characteristics of the landslide is conducted to explore its impact on transportation infrastructure, thereby significantly improving the temporal resolution and accuracy of landslide monitoring. To verify the feasibility of the algorithm, this paper selects the Gaojiawan landslide as a typical study area. Based on the ascending and descending Sentinel-1 SAR data from 2016 to 2023, it extracts the temporal series of slope body deformation to further explore its impact on the internal transportation infrastructure of the slope body. Experimental results show that the combination of ascending and descending SAR data and Kalman filtering has improved the time resolution of landslide monitoring to six days. It was found that two significant slips occurred in the slope body in January 2016 and June 2021, while other periods were relatively stable. Further discussion and analysis reveal that there is a difference in the slip deformation rate between the upper and lower parts of the slope body, and the shear stress caused by dislocation deformation.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11687915 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0316100 | PLOS |
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